Difference between revisions of "Wu and Weld WWW 2008"
| Line 13: | Line 13: | ||
The autonomous system, presented as Kylin Ontology Generator (KOG), is comprised of three modules: | The autonomous system, presented as Kylin Ontology Generator (KOG), is comprised of three modules: | ||
| − | * | + | * a schema cleaner, which merges duplicate classes and attributes and prunes rarely-used ones, |
| − | * | + | * a subsumption detector, which identifies "IS-A" relations between infobox classes (e.g. "volleyball player" IS-A "athlete"), |
| − | * | + | * and a schema mapper, which builds attribute mappings between related infobox classes. |
== Experimental result == | == Experimental result == | ||
Revision as of 15:19, 25 September 2011
Citation
Wu, F. and Weld, D. 2008. Automatically Refining the Wikipedia Infobox Ontology. In Proceedings of the 17th Conference of the World Wide Web, pp. 635-644, ACM, New York.
Online version
Summary
This is a paper that introduces an autonomous system for refining Wikipedia’s infobox information schema to create a cleanly-structured ontology. Advanced query capability, improved information extractors and semiautomatic generation of new infobox templates are shown as advantages of a refined ontology. The ontology refinement problem is solved using both Support Vector Machines and a more powerful joint-inference approach expressed in Markov Logic Networks.
The autonomous system, presented as Kylin Ontology Generator (KOG), is comprised of three modules:
- a schema cleaner, which merges duplicate classes and attributes and prunes rarely-used ones,
- a subsumption detector, which identifies "IS-A" relations between infobox classes (e.g. "volleyball player" IS-A "athlete"),
- and a schema mapper, which builds attribute mappings between related infobox classes.
Experimental result
...
Related papers
This paper is based on Wu and Weld CIKM 2007.
